omputational science adds a new dimension to the more traditional experimental and theoretical approaches to scientific research. The use of computational tools has become vital to most fields of science and engineering and to many parts of the educational enterprise.

High-speed, large-scale computation has become the primary technology enabling advanced research in many areas of science and engineering. For this reason, blue-ribbon panels studying U.S. technological competitiveness have emphasized the critical importance of furthering our nation's traditional lead in high-performance computing technology.

Indeed, in many applications of interest to DOE and ORNL, computer simulations are the only feasible method of scientific investigation. Conventional methods would require prohibitively expensive experimental facilities and decades of effort. Leadership in this area requires the capacity to integrate advanced mathematical and computational techniques, data management and analysis methods, software tools, communications technologies, and high-performance computing systems.

At ORNL, we focus our strengths on scientific Grand Challenges and other highly complex computing issues. How? We integrate expertise in basic and applied research with the outstanding high-performance computing systems and infrastructure of our Center for Computational Sciences. Our strengths range from the ability to develop realistic mathematical models of complex phenomena and scalable algorithms for their solution to the availability of massively parallel processors and storage systems accessed by high-performance computing environments.

ORNL has long been a leader in computational plasma physics and materials science, nuclear physics and transport calculations, matrix computations, geographic information systems, and environmental information management. More recently, the Laboratory has become a leader in algorithms for parallel computers, informatics with emphasis on biosciences, global climate simulations, groundwater contaminant transport, distributed computing tools and interfaces, high-performance parallel computers, and data storage systems.

As a result of this leadership, we're working closely with major universities and with both computer and applications industries to conduct collaborative research and to commercialize technology. Automobile manufacturers, for example, are sponsoring computerized car-crash simulations at ORNL. And oil and aerospace companies are relying on ORNL's parallel virtual machine software to solve some of their most complex problems by linking and metrogeneous computers into high-performance, high-speed unified systems.

These errors make it difficult to identify proteins, which are made of various combinations of amino acids. Each of the 20 amino acids is coded for by a particular group of three bases. So, a sugar-digesting enzyme
that contains 300 amino acids is a product of 900 bases. The base sequence, or nucleic acid alphabet, spells out the protein's amino-acid sequence, or protein sequence.

If a base is erroneously missing in the sequence, the groups of three bases coding for each amino acid will fall out of sequencea frame shift. Multiple frame shifts could prevent identification of a protein by its sequence. Repeating the sequencing 10 times allows accurate identification, but it's expensive.

To cut costs, ORNL has developed a frame-shift-tolerant protein sequence comparison algorithm that accurately detects proteins from a one-time DNA sequence. This step-by-step computerized procedure compares the experimental sequence with sequences in a database, considers all possibilities for errors, and finds the best match. In this way, proteins can be identified from corrupted sequences and errors can be determined.

The algorithm is part of the recently released Version 1.3 of the
Gene Recognition and Analysis Internet Link (GRAIL) system, which is used
by more than 1000 biomedical laboratories and biotechnology
firms. The ORNL-developed GRAIL, which uses statistical analysis to
separate meaningful words from genetic gibberish, finds genes in
sequences through pattern recognition and through database comparisons
for which the new algorithm is used. Recently, GRAIL pinpointed a
gene responsible for a genetic disorder that can lead to paralysis, muteness,
and death in boysa theme of the movie
Lorenzo's Oil.

Funding for this research has come from DOE's Office of Health and Environmental Research.

Mona Yethiraj, an ORNL scientist, checks a small-angle neutron scattering spectrometer that will be operated remotely for neutron science experiments at ORNL's High Flux Isotope Reactor.

ORNL and other DOE national laboratories are implementing the DOE 2000 program by establishing
a remotely accessible environment through video links, cameras, interactive laboratory notebooks,
and software to control instruments, adjust samples, and view and manipulate data from home pages of the Internet's World Wide Web. Two ORNL user facility instruments have been put on line for remote operation. They are the HF 2000 cold field-emission transmission electron microscope at the High Temperature Materials Laboratory and a small-angle neutron scattering spectrometer at the
High Flux Isotope Reactor (HFIR). By late 1996 we hope to have widely scattered non-ORNL users examining the structure of specimens and doing neutron scattering experiments over the network. We hope they find collaborative research from a distance as pleasant, effective, and collegial as that on site.

In this holographic representation of a computational simulation of a nano-device the size of a dust mote, the tube is formed from carbon atoms (blue tennis balls), the soccer ball is a buckyball, and the green squash balls are flowing helium atoms that penetrate and push the buckyball "piston" through the tube.

When you hold ORNL's plastic card for guests to the lightthe Kodamotion card made by Kodakyou see what looks like a soccer ball and a few green squash balls rolling in a tube made up of blue tennis
balls glued together. In this holographic representation of a computational simulation of a nanodevice (from nanometer, a billionth of a meter), the tube is formed from carbon atoms, the soccer ball is a buckyball, and
the green balls are flowing helium atoms that can penetrate and push the buckyball "piston" through the tube. By turning the Kodamotion card slowly, you see interactions among all the atoms, even the naturally vibrating "balls" in the graphite tube.

Nanotechnology futurists dream of microbe-sized machines built from a few million atoms. They envision robots the size of a dust mote that manufacture therapeutic drugs or swim along eating stream pollutants
or slaying cancer cells in the bloodstream. They envision "smart" materials embedded with nanosensors that alert operators to atomic-level defects, providing adequate time to repair or replace equipment before it can fail. Already on the scene are "optical tweezers"laser beams that spin microscopic rotors in liquid and can be used to dissect bacteria and manipulate molecules at room temperature.

We have developed computational tools to do reality checks on designs for nano-scale devices.

But will the dreamers' designs work as intended? Will the devices be stable? What are their operational limits? Our chemical physicists have developed tools to do reality checks on these ideas. They have adapted algorithms to solve molecular dynamics equations quickly on parallel computersin a minute for every hour previously required. Now, computational simulations of the mechanical properties of molecular bearings and gears are feasible. Interactions of a gas, liquid, or laser light with a nanomachine part can be precisely modeled.

Computational simulations can lead to new discoveries. ORNL's simulation of a design for a nano-scale "frictionless" bearing revealed the new phenomenon of atomic-scale friction, suggesting that a redesign is needed to reduce this effect.

Our chemical physicists are now working under a CRADA with Angstrom Tools, LLC, to develop user-friendly software to design and test proposed nanostructures and devices. They are convinced that
practical nanomachines are in the cards.

The research has been supported by a grant from ORNL's Laboratory Directed Research and Development Fund and by DOE's Office of Energy Research, Basic Energy Sciences, Materials Sciences Division.